When one is listening to someone or something, disturbing noise or unwanted acoustic signals are present everywhere that interfere with the other person's voice or with a wanted acoustic signal. People with a hearing impairment are especially susceptible to such noise interference. Background conversations, acoustic disturbance from digital devices (cell phones), traffic or other environmental noise can make it very difficult for a hearing-impaired person to understand the speaker they want to listen to. Reducing the noise level in an acoustic signal, combined with automatic focusing on a wanted acoustic signal component, can significantly improve the efficiency of an electronic speech processor of the type used in modern hearing aids.
Hearing aids employing digital signal processing have recently been introduced. They contain one or more microphones, A/D converters, digital signal processors, and loudspeakers. The digital signal processors usually subdivide the incoming signals into a plurality of frequency bands. Within each of these bands, signal amplification and processing can be individually matched to the requirements of a particular hearing aid wearer in order to improve the intelligibility of a particular component. Also available in connection with digital signal processing are algorithms for minimizing feedback and interference noise, although these have significant disadvantages. The disadvantageous feature of the algorithms currently employed for minimizing interference noise is, for example, the maximum improvement they can achieve in hearing-aid acoustics when speech and background noise are within the same frequency region, making them incapable of distinguishing between spoken language and background noise. (See also EP 1 017 253 A2).
This is one of the most frequently occurring problems in acoustic signal processing, namely extracting one or more acoustic signals from different overlapping acoustic signals. It is also known as the “cocktail party problem”, wherein all manner of different sounds such as music and conversations merge into an indefinable acoustic backdrop. Nevertheless, people generally do not find it difficult to hold a conversation in such a situation. It is therefore desirable for hearing aid wearers to be able to converse in just such situations in the same way as people without a hearing impairment.
EP 1 432 282 A2 discloses a digital method for adjusting a hearing program of a hearing device to an instantaneous acoustic ambient situation, and a hearing device system for this purpose. With this method, in a digital signal analysis unit of the hearing device, characteristic auditory-based features are extracted from a digital acoustic signal and analyzed by a pattern recognizer in a signal identification unit to determine an acoustic ambient situation and generate a corresponding acoustic output signal. Said acoustic output signal is fed to a transmission unit that can be manipulated by an input unit such as a remote control, it being possible for preset parameter sets of the transmission unit to be influenced by a hearing aid wearer's input unit.
In acoustic signal processing there exist spatial (e.g. directional microphone, beam forming), statistical (e.g. blind source separation), and hybrid methods which, by means of algorithms and otherwise, are able to separate out one or more sound sources from a plurality of simultaneously active sound sources. For example, by means of statistical signal processing of at least two microphone signals, blind source separation enables source signals to be separated without prior knowledge of their geometric arrangement. When applied to hearing aids, that method has advantages over conventional approaches involving a directional microphone. Using a BSS (Blind Source Separation) method of this kind it is inherently possible, with n microphones, to separate up to n sources, i.e. to generate n output signals.
Known from the relevant literature are blind source separation methods wherein sound sources are analyzed by analyzing at least two microphone signals. A method and corresponding device of this kind are known from EP 1 017 253 A2, the scope of whose disclosure is expressly to be included in the present specification. Corresponding points of linkage between the invention and EP 1 017 253 A2 are indicated mainly at the end of the present specification.
In a specific application for blind source separation in hearing aids, this requires communication between two hearing devices (analysis of at least two microphone signals (right/left)) and preferably binaural evaluation of the signals of the two hearing devices which is preferably performed wirelessly. Alternative couplings of the two hearing devices are also possible in such an application. Binaural evaluation of this kind with stereo signals being provided for a hearing aid wearer is taught in EP 1 655 998 A2, the scope of whose disclosure is likewise to be included in the present specification. Corresponding points of linkage between the invention and EP 1 655 998 A2 are indicated at the end of the present specification.
Directional microphone control in the context of blind source separation is subject to ambiguity once a plurality of competing wanted sources, e.g. speakers, are simultaneously present. While blind source separation basically allows the different sources to be separated, provided they are spatially separate, the potential benefit of a directional microphone is reduced by said ambiguity problems, although a directional microphone can be of great benefit in improving speech intelligibility specifically in such scenarios.
The hearing aid or more particularly the mathematical algorithms for blind source separation is/are basically faced with the dilemma of having to decide which of the signals produced by blind source separation can be most advantageously forwarded to the algorithm user, i.e. the hearing aid wearer. This is basically an unresolvable problem for the hearing aid because the choice of wanted acoustic source will depend directly on the hearing aid wearer's momentary intention and hence cannot be available to a selection algorithm as an input variable. The selection made by said algorithm must accordingly be based on assumptions about the listener's likely intention.
The prior art is based on the assumption that the hearing aid wearer prefers an acoustic signal from a 0° direction, i.e. from the direction in which the hearing aid wearer is looking. This is realistic insofar as, in an acoustically difficult situation, the hearing aid wearer would look at his/her current interlocutor to obtain further cues (e.g. lip movements) for increasing said interlocutor's speech intelligibility. This means that the hearing aid wearer is compelled to look at his/her interlocutor so that the directional microphone will produce increased speech intelligibility. This is annoying particularly when the hearing aid wearer wants to converse with just one person, i.e. is not involved in communicating with a plurality of speakers, and does not always wish/have to look at his/her interlocutor.
If the direction of the wanted sound is not set to 0° for the hearing aid, ambiguity can be resolved by other additional information, e.g. by giving preference to the acoustic signal arriving with an angle of incidence that is as small as possible with respect to the forward direction. However, this severely restricts the hearing aid wearer's freedom of movement. It also creates the potential problem of ‘jumping’ between different speakers, which is unintended and experienced as unpleasant by the hearing aid wearer.
Furthermore, there is to date no known technical method for making a “correct” choice of acoustic source, or more specifically one preferred by the hearing aid wearer, after source separation has taken place.